[en] Many countries have pledged to reduce greenhouse gases. In this context, the dairy sector is one of the identified sectors to adapt production circumstances to address socio-environmental constraints due to its large carbon footprint related to CH4 emission. This study aimed mainly to estimate (1) the genetic parameters of 2 milk mid-infrared-based CH4 proxies [predicted daily CH4 emission (PME, g/d), and log-transformed predicted CH4 intensity (LMI)] and (2) their genetic correlations with milk production traits [milk (MY), fat (FY), and protein (PY) yields] from first- and second-parity Holstein cows. A total of 336,126 and 231,400 mid-infrared CH4 phenotypes were collected from 56,957 and 34,992 first- and second-parity cows, respectively. The PME increased from the first to the second lactation (433 vs. 453 g/d) and the LMI decreased (2.93 vs. 2.86). We used 20 bivariate random regression test-day models to estimate the variance components. Moderate heritability values were observed for both CH4 traits, and those values decreased slightly from the first to the second lactation (0.25 ± 0.01 and 0.22 ± 0.01 for PME; 0.18 ± 0.01 and 0.17 ± 0.02 for LMI). Lactation phenotypic and genetic correlations were negative between PME and MY in both first and second lactations (−0.07 vs. −0.07 and −0.19 vs. −0.24, respectively). More close scrutiny revealed that relative increase of PME was lower with high MY levels even reverting to decrease, and therefore explaining the negative correlations, indicating that higher producing cows could be a mitigation option for CH4 emission. The PME phenotypic correlations were almost equal to 0 with FY and PY for both lactations. However, the genetic correlations between PME and FY were slightly positive (0.11 and 0.12), whereas with PY the correlations were slightly negative (−0.05 and −0.04). Both phenotypic and genetic correlations between LMI and MY or PY or FY were always relatively highly negative (from −0.21 to −0.88). As the genetic correlations between PME and LMI were strong (0.71 and 0.72 in first and second lactation), the selection of one trait would also strongly influence the other trait. However, in animal breeding context, PME, as a direct quantity CH4 proxy, would be preferred to LMI, which is a ratio trait of PME with a trait already in the index. The range of PME sire estimated breeding values were 22.1 and 29.41 kg per lactation in first and second parity, respectively. Further studies must be conducted to evaluate the effect of the introduction of PME in a selection index on the other traits already included in this index, such as, for instance, fertility or longevity.
Disciplines :
Genetics & genetic processes Animal production & animal husbandry
Froidmont, Eric; Centre wallon de recherches agronomiques - CRA-W
Gengler, Nicolas ; Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Ingénierie des productions animales et nutrition
Soyeurt, Hélène ; Université de Liège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Modélisation et développement
Language :
English
Title :
Genetic parameters of mid-infrared methane predictions and their relationships with milk production traits in Holstein cattle
Alternative titles :
[en] Paramètres génétiques des prédictions de méthane prédites par moyen infrarouge et leurs relations avec les caractères laitiers dans la population Holstein
Publication date :
June 2017
Journal title :
Journal of Dairy Science
ISSN :
0022-0302
eISSN :
1525-3198
Publisher :
American Dairy Science Association, Champaign, United States - Illinois
Bastin, C., Soyeurt, H., Gengler, N., Genetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1–3. J. Anim. Breed. Genet. 130 (2013), 118–127 23496012.
Cassandro, M., Cecchinato, A., Battagin, M., Penasa, M., Genetic parameters of methane production in Holstein Friesian cows. In Proceeding of the 9th World Congress on Genetics Applied to Livestock Production (WCGALP), 2010, German Society for Animal Production, Bonn, Germany Leipzig, Germany.
Chilliard, Y., Martin, C., Rouel, J., Doreau, M., Milk fatty acids in dairy cows fed whole crude linseed, extruded linseed, or linseed oil, and their relationship with methane output. J. Dairy Sci. 92 (2009), 5199–5211 19762838.
de Haas, Y., Windig, J.J., Calus, M.P.L., Dijkstra, J., de Haan, M., Bannink, A., Veerkamp, R.F., Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. J. Dairy Sci. 94 (2011), 6122–6134 22118100.
Dehareng, F., Delfosse, C., Froidmont, E., Soyeurt, H., Martin, C., Gengler, N., Vanlierde, A., Dardenne, P., Potential use of milk mid-infrared spectra to predict individual methane emission of dairy cows. Animal 6 (2012), 1694–1701 23031566.
Dijkstra, J., van Zijderveld, S.M., Apajalahti, J.A., Bannink, A., Gerrits, W.J.J., Newbold, J.R., Perdok, H.B., Berends, H., Relationships between methane production and milk fatty acid profiles in dairy cattle. Anim. Feed Sci. Technol. 166 (2011), 590–595.
Dong, L.F., Yan, T., Ferris, C.P., McDowell, D.A., Gordon, A., Is there a relationship between genetic merit and enteric methane emission rate of lactating Holstein-Friesian dairy cows?. Animal 9 (2015), 1807–1812 26264038.
Enriquez-Hidalgo, D., Gilliland, T., Deighton, M.H., O'Donovan, M., Hennessy, D., Milk production and enteric methane emissions by dairy cows grazing fertilized perennial ryegrass pasture with or without inclusion of white clover. J. Dairy Sci. 97 (2014), 1400–1412 24393178.
Fischer, T.M., Gilmour, A.R., van der Werf, J.H.J., Computing approximate standard errors for genetic parameters derived from random regression models fitted by average information REML. Genet. Sel. Evol. 36 (2004), 363–369 15107271.
Garnsworthy, P.C., Craigon, J., Hernandez-Medrano, J.H., Saunders, N., Variation among individual dairy cows in methane measurements made on farm during milking. J. Dairy Sci. 95 (2012), 3181–3189 22612953.
Gerber, P.J., Steinfeld, H., Henderson, B., Mottet, A., Opio, C., Dijkman, J., Falcucci, A., Tempio, G., Tackling climate change through livestock—A global assessment of emissions and mitigation opportunities, 2013, FAO, Rome, Italy.
Kandel, P.B., Gengler, N., Soyeurt, H., Assessing variability of literature based methane indicators traits in a large dairy cow population. Biotechnol. Agron. Soc. Environ. 19 (2015), 11–19.
Kandel, P.B., Vanrobays, M.-L., Vanlierde, A., Dehareng, F., Froidmont, E., Dardenne, P., Lewis, E., Buckley, F., Deighton, M.H., McParland, S., Gengler, N., Soyeurt, H., Genetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows. Page 279 in Proc. Adv. Anim. Biosci. (5th Greenhouse Gases Animal Agriculture Conference), 2013, Cambridge Journals, Cambridge, UK.
Lassen, J., Løvendahl, P., Heritability estimates for enteric methane production in dairy cattle using non-invasive methods. J. Dairy Sci. 99 (2016), 1959–1967 26805978.
Martin, C., Rouel, J., Jouany, J.P., Doreau, M., Chilliard, Y., Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil. J. Anim. Sci. 86 (2008), 2642–2650 18469051.
Misztal, I., BLUPF90 family of programs, 2012 Accessed Oct. 2013. http://nce.ads.uga.edu/wiki/doku.php?id=application_programs.
Moate, P.J., Richard, S., Williams, O., Deighton, M.H., Pryce, J.E., Hayes, B.J., Jacobs, J.L., Eckard, R.J., Hannah, M.C., Wales, W.J., Mitigation of enteric methane emissions from the Australian dairy industry. Pages 121–140 in Proc. 5th Australasian Dairy Symp., 2014, Australian Dairy Science Symposium, Narellan, Australia Hamilton, New Zealand.
Pickering, N.K., Chagunda, M.G.G., Banos, G., Mrode, R., McEwan, J.C., Wall, E., Genetic parameters for predicted methane production and laser methane detector measurements. J. Anim. Sci. 93 (2015), 11–20 25403186.
Soyeurt, H., Dardenne, P., Dehareng, F., Bastin, C., Gengler, N., Genetic parameters of saturated and monounsaturated fatty acid content and the ratio of saturated to unsaturated fatty acids in bovine milk. J. Dairy Sci. 91 (2008), 3611–3626 18765620.
Soyeurt, H., Dehareng, F., Gengler, N., McParland, S., Wall, E., Berry, D.P., Coffey, M., Dardenne, P., Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries. J. Dairy Sci. 94 (2011), 1657–1667 21426953.
van Engelen, S., Bovenhuis, H., Dijkstra, J., van Arendonk, J.A.M., Visker, M.H.P.W., Genetic study of methane production predicted from milk fat composition in dairy cows. J. Dairy Sci. 98 (2015), 8223–8226 26364110.
van Lingen, H.J., Crompton, L.A., Hendriks, W.H., Reynolds, C.K., Dijkstra, J., Meta-analysis of relationships between enteric methane yield and milk fatty acid profile in dairy cattle. J. Dairy Sci. 97 (2014), 7115–7132 25218750.
Vanlierde, A., Vanrobays, M.-L., Dehareng, F., Froidmont, E., Soyeurt, H., McParland, S., Lewis, E., Deighton, M.H., Grandl, F., Kreuzer, M., Gredler, B., Dardenne, P., Gengler, N., Innovative lactation-stage-dependent prediction of methane emissions from milk mid-infrared spectra. J. Dairy Sci. 98 (2015), 5740–5747 26026761.
Vanlierde, A., Vanrobays, M.-L., Gengler, N., Dardenne, P., Froidmont, E., Soyeurt, H., McParland, S., Lewis, E., Deighton, M.H., Mathot, M., Grandl, F., Kreuzer, M., Gredler, B., Dehareng, F., Milk mid-infrared spectra enable prediction of lactation-stage dependent methane emissions of dairy cattle within routine population-scale milk recording schemes. Anim. Prod. Sci. 56 (2016), 258–264.
Veneman, J.B., Muetzel, S., Hart, K.J., Faulkner, C.L., Moorby, J.M., Perdok, H.B., Newbold, C.J., Does dietary mitigation of enteric methane production affect rumen function and animal productivity in dairy cows?. PLoS One, 10, 2015, e0140282 26509835.
Wall, E., Simm, G., Moran, D., Developing breeding schemes to assist mitigation of greenhouse gas emissions. Animal 4 (2010), 366–376 22443941.
Wathes, D.C., Bourne, N., Cheng, Z., Mann, G.E., Taylor, V.J., Coffey, M.P., Multiple correlation analyses of metabolic and endocrine profiles with fertility in primiparous and multiparous cows. J. Dairy Sci. 90 (2007), 1310–1325 17297107.
Wollenberg, E., Richards, M., Smith, P., Havlik, P., Obersteiner, M., Tubiello, F.N., Herold, M., Gerber, P., Carter, S., Resinger, A., van Vuuren, D.P., Dickie, A., Neufeldt, H., Sander, B.O., Wassmann, R., Sommer, R., Amonette, J.E., Falcucci, A., Herrero, M., Opio, C., Roman-Cuesta, R.M., Stehfestn, E., Westhoek, H., Ortiz-Monasterio, I., Sapkota, T., Rufino, M.C., Thornton, P.K., Verchot, L., West, P.C., Soussana, J.-F., Baedeker, T., Sadler, M., Vermeulen, S., Campbell, B.M., Reducing emissions from agriculture to meet 2°C target. Glob. Change Biol. 22 (2016), 3859–3864 27185416.